Transport of Semivolatile Organic Compounds to the Tibetan Plateau: Spatial and Temporal Variation in Air Concentrations in Mountainous Western Sichuan, China
Bibliographic record
Abstract
The distribution of organochlorine pesticides and polychlorinated biphenyls in air along an altitudinal transect on Balang Mountain in western China was measured by deploying XAD-2 resin based passive air samplers in duplicate at seven sites with elevations ranging from 1242 to 4485 m above sea level for five consecutive six-month periods between 2005 and 2008. Analyzed by gas chromatography-high resolution mass spectrometry, concentrations of hexachlorobenzene were highest, followed by hexachlorocyclohexanes, DDT-related compounds and PCB congeners 28 and 52. Except for hexachlorobenzene, which had largely uniform concentrations in space and time, there were clear seasonal variations with concentrations in summer being higher than in winter. With a few exceptions, concentrations that vary little with altitude suggest that the presence of these chemicals in the area is almost entirely due to atmospheric transport, most likely from the Chengdu plain. This is supported by similarities in the relative abundance of different compounds and in the differences between summer and winter concentrations measured in the city of Chengdu and in the mountains. Furthermore, air mass trajectories during the sampling period often originate to the East, passing over the Western part of the Sichuan basin, including the Chengdu plain, prior to arriving at the sampling sites. Higher summer time values in the mountains are due to more contaminated air being blown into the region, presumably due either to higher pesticide usage in summer or due to higher temperatures leading to higher evaporation in source regions. Air and soil from the region are in equilibrium with respect to alpha-HCH, gamma-HCH, and HCB, whereas a situation of net deposition prevails for p,p'-DDE and p,p'-DDT.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".